import matplotlib.pyplot as plt

decisionNode = dict(boxstyle="sawtooth", fc="0.8")
leafNode = dict(boxstyle="round4", fc="0.8")
arrow_args = dict(arrowstyle="<-")



'''绘制树节点'''
# def createPlot():
#     fig = plt.figure(1, facecolor='white')
#     fig.clf()
#     createPlot.ax1 = plt.subplot(111, frameon=False)
#     plotNode('a decision node', (0.5, 0.1), (0.1, 0.5), decisionNode)
#     plotNode('a leaf node', (0.8, 0.1), (0.3, 0.8), leafNode)
#     plt.show()


def plotNode(nodeText, centerPt, parentPt, nodeType):
    createPlot.ax1.annotate(nodeText,
                            xy=parentPt,
                            xycoords="axes fraction",
                            xytext=centerPt, textcoords="axes fraction",
                            va="center", ha='center', bbox=nodeType, arrowprops=arrow_args)

'''获取叶节点数目'''
def getNumLeafs(myTree):
    numLeafs = 0
    firstStr = list(myTree.keys())[0]
    secondDict = myTree[firstStr]
    for key in secondDict.keys():
        # test to see if the nodes are dictionaries, if not they are leaf nodes
        if type(secondDict[key]).__name__=='dict':
            numLeafs += getNumLeafs(secondDict[key])
        else:
            numLeafs += 1
    return numLeafs

'''获取树的深度'''
def getTreeDepth(myTree):
    maxDepth = 0
    firstStr = list(myTree.keys())[0]
    secondDict = myTree[firstStr]
    for key in secondDict.keys():
        # test to see if the nodes are dictionaries, if not they are leaf nodes
        if type(secondDict[key]).__name__=='dict':
            thisDepth = 1 + getTreeDepth(secondDict[key])
        else:
            thisDepth = 1
        if thisDepth > maxDepth:
            maxDepth = thisDepth
    return maxDepth

'''输出预先存储的树信息'''
def retrieveTree(i):
    listOfTrees = [
        {'no surfacing': {0: 'no',
                          1: {'flippers': {0: 'no',
                                           1: 'yes'}}}},
        {'no surfacing': {0: 'no',
                          1: {'flippers': {0: {'head': {0: 'no',
                                                        1: 'yes'}},
                                           1: 'no'}}}}
    ]
    return listOfTrees[i]


'''plot Tree'''
def plotMidText(cntrPt, parentPt, txtString):
    xMid = (parentPt[0] - cntrPt[0])/2.0 + cntrPt[0]
    yMid = (parentPt[1] - cntrPt[1])/2.0 + cntrPt[1]
    createPlot.ax1.text(xMid, yMid, txtString, va='center', ha='center', rotation=30)


def plotTree(myTree, parentPt, nodeText):
    numLeafs = getNumLeafs(myTree)
    depth = getTreeDepth(myTree)
    firstStr = list(myTree.keys())[0]
    cntrPt = (plotTree.x0ff + (1.0 + float(numLeafs))/2.0/plotTree.totalW, plotTree.y0ff)
    plotMidText(cntrPt, parentPt, nodeText)
    plotNode(firstStr, cntrPt, parentPt, decisionNode)
    secondDict = myTree[firstStr]
    plotTree.y0ff = plotTree.y0ff - 1.0/plotTree.totalD
    for key in secondDict.keys():
        if type(secondDict[key]).__name__=='dict':
            plotTree(secondDict[key], cntrPt, str(key))
        else:
            plotTree.x0ff = plotTree.x0ff + 1.0/plotTree.totalW
            plotNode(secondDict[key], (plotTree.x0ff, plotTree.y0ff), cntrPt, leafNode)
            plotMidText((plotTree.x0ff, plotTree.y0ff), cntrPt, str(key))
    plotTree.y0ff = plotTree.y0ff + 1.0/plotTree.totalD


def createPlot(inTree):
    fig = plt.figure(1, facecolor='white')
    fig.clf()
    axprops = dict(xticks=[], yticks=[])
    createPlot.ax1 = plt.subplot(111, frameon=False, **axprops)
    plotTree.totalW = float(getNumLeafs(inTree))
    plotTree.totalD = float(getTreeDepth(inTree))
    plotTree.x0ff = -0.5/plotTree.totalW; plotTree.y0ff = 1.0
    plotTree(inTree, (0.5, 1.0), '')
    plt.show()


# myTree = retrieveTree(1)
#
# createPlot(myTree)
